References
- MND, "Materials for the Development and Integration Platform of Predictive Maintenance Technology," pp. 3-6, 2021.12.1.
- MND, "Establishment of Big Data Collection / Analysis System for Military Logistics BPR/ISP", pp. 23, 2021.12.9.
- MND, "Report on the Technical Level and Applicability of Weapon System Sensor Data", pp. 3-5, 2021.4.2.
- Ministry of National Defense, "Implementation Plan for the Establishment of Big Data for Military Logistics", pp. 7-10, 2020.11.4.
- Kyung-Won Oh, "Development of Korean Condition-Based Maintenance Systems to Monitor Naval Weapon Systems", International Journal of Aerospace System Engineering, pp. 67-68, 2016. http://dx.doi.org/10.20910/JASE.2016.10.4.67
- Ki-Jung Kim et al. 3, "A Study on the Application Plan of Aircraft CBM+ in the Air Force", Air Force Headquarters, pp. 1-5, 2018.10.16.
- Keun-Young Kim et al. 3, "Roadmap Configuration for Technical Elements Acquisition of Military Fixed Wing Aircraft Parts PHM and Verification of Parts Selection Phase", International Journal of Aeronautical and Space Sciences, pp. 674-677, September 2019.9. http://dx.doi.org/10.5139/JKSAS.2019.47.9.665
- Dong-Hoon Kim et al. 2, "Analysis of High-Speed Fourier Transform for Submarine Major Equipment Vibration and Application of Predictive Maintenance", Journal of the KNST, pp. 20-21, 2021.
- Gyu-Seon Cho, "A Study on the Depot Maintenance Effects of CBM+ Model Application for Transmission in Tracked Vehicle with Missile System", Daejeon University, pp. 1-5, 2021.4.
- Baek-Chun Shin, "A Study on the Application Methodology of CBM+ in the Early Design Stage of Weapon Systems", Kumoh National Institute of Technology, pp. 1-5, 2022.
- Do-Hyun Jeong et al.3, "Real-time Life Prediction of Engine Oil in Moving Equipment with Different Main Systems and Operating Times", 2022 Proceedings of the KIMST Comprehensive Academic Conference, pp. 110, 2022.6.9.
- Alfonsus Julanto Endharta et al.4, "Study on Effectiveness of CBM+ in Weapons Systems through RAM-C Analysis", Journal of the KAIS, pp. 249-251, 2023. http://dx.doi.org/10.5762/KAIS.2023.24.9.249